...The Role Of Research and Statistics In Psychology Statistical Reasoning in Psychology Research and Statistics in Psychology Research and Statistics play an important role in psychology. Researchers in the field of psychology study what people will do or how they will react in any situation. Since not everyone reacts the same to a certain situation, statistics is used to see if a certain action happens often enough to come to an idea about cause and effect. It used to be believed that statistics could prove anything (Helberg). This is not true. It would only be found true if the researcher used statistics improperly and tried to bend the rules to validate their view on the subject matter (Helberg). Research and Statistics have many different areas that prove important for psychology. Statistics Statistics refers to techniques and procedures for analyzing and interpreting data, displaying data and decisions made based on the data collected. In Statistics there are different areas to be able to find and explain certain types of things being researched. There is inferential statistics, descriptive statistics, variables, parameters, summation notation and measurement scales. Statistics which is often considered confusing can be cleared up with explanation and examples of each area. Descriptive Statistics is a summary of the collected data. It helps to organize it in a way that makes it understandable. An example would be: A personality test on 1000 college...
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...Basic Concepts in Positive Psychology Stuart Zarahn PSY/220 Alan Coffin 05/29/2015 Researchers refer to’ Subjective Well- Being’ as how people experience the quality of their lives, and includes both emotional and cognitive judgements. They have defined ‘happiness’ as a combination of life’s satisfactions and how frequently we experience positive and negative effects. SWB includes our mood swings and emotions, as well as an overall satisfaction of our lives. Basically, subjective well-being is the positive and negative things that happen to us, how frequently they occur, the importance as they pertain to our happiness or sadness, and are linked to our personality traits. Everyone responds in their own way to a crisis or to a joyful event, so how and why we respond depends upon our personalities. John Lennon said it best, “Life is what happens to you while you’re busy making other plans” As far as being hooked up to a feel great all the time machine, if it was temporary like the “orgasmatron” in Woody Allen’s movie, or having a tube in my mouth that was attached to a tank of nitrous oxide (reality for me in 1970), then sure, why not? If it is a permanent situation, then no thank you. I might as well be in a catatonic state, feeling no emotions, pain, or joy, disconnected from reality or in a coma. All social interactions would be gone as I sat there with a perpetual stupid grin. I knew a girl named ‘Frankie’ who dropped a lot of LSD back in the late 60’s, early 70’s...
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...DQ 1: What are some terms related to hypothesis testing that you are already familiar with? What is the difference between a null and an alternative hypothesis statement? Why do a null and alternative hypothesis have to be mutually exclusive? (Due Wednesday) Terms that is related to hypothesis testing that I am familiar with is hypothesis, which means a prediction which is usually based on an informal observation, research and it is tested in a study. Theory is another term I know. Theory is what one has or a set of principles that tries to explain one or more facts. I did not know there was something called null hypothesis. According to our textbook, “null hypothesis” is because it “states the situation in which there is no difference ( the difference is null) between the populations” (Aron, Aron, & Coups, 2009). Null hypothesis will show that there is no observed effect for a experiment. A null hypothesis is what one tries to overturn his or her hypothesis test. Taylor (2013) states, “We hope to obtain a small enough p-value that we are justified in rejecting the null hypothesis” (para. 3). A alternative hypothesis is also known as an experimental hypothesis. It shows that there is a observed effect for an experiment. It is what one tries to show in an indirect way by using the hypothesis testing. If the null hypothesis is rejected then one will see that the alternative hypothesis is effective. Now if the finding are not null then one will not accept the alternative of the...
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...Name: Unknown Chapter 4 Instructions Practice Problem 11, 14, & 18 Due Week 4 Day 6 (Sunday) Follow the instructions below to submit your answers for Chapter 4 Practice Problem 11, 14 & 18. 1. Save Chapter 4 Instructions to your computer. 2. Type your answers into the shaded boxes below. The boxes will expand as you type your answers. 3. Resave this form to your computer with your answers filled-in. 4. Attach the saved form to your reply when you turn-in your work in the Assignments section of the Classroom tab. Note: Each question in the assignments section will be listed separately; however, you only need to submit this form one time to turn-in your answers. Read each question in your text book and then type your answers for Chapter 4 Practice Problem 11, 14 & 18 in the shaded boxes below. Please record only your answers. It is not necessary to show your work. 11. Step 1 – Restate the research question; specify the null theory about the populations. - This is step is necessary because it is a reference point throughout the study. Always state the null theory and the alternate theory Null - Ho: Alternate - Ha: Step 2 – Determine the features of the compared distribution. Define the level of significance, using type 1 errors; identify sample size using data and resources that are available. Step 3 – Find out the sample’s score on the comparison distribution. Once the sample outcomes are the Z score can be computed as under: is...
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...University of Phoenix Material Week 4 Practice Worksheet Prepare a written response to the following questions. Chapters 9 &11 1. Two boats, the Prada (Italy) and the Oracle (USA), are competing for a spot in the upcoming America’s Cup race. They race over a part of the course several times. The sample times in minutes for the Prada were: 12.9, 12.5, 11.0, 13.3, 11.2, 11.4, 11.6, 12.3, 14.2, and 11.3. The sample times in minutes for the Oracle were: 14.1, 14.1, 14.2, 17.4, 15.8, 16.7, 16.1, 13.3, 13.4, 13.6, 10.8, and 19.0. For data analysis, the appropriate test is the t-Test: Two-Sample Assuming Unequal Variances. The next table shows the results of this independent t-test. At the .05 significance level, can we conclude that there is a difference in their mean times? Explain these results to a person who knows about the t test for a single sample but is unfamiliar with the t test for independent means. Hypothesis Test: Independent Groups (t-test, unequal variance) Prada Oracle 12.170 14.875 mean 1.056 2.208 std. dev. 10 12 n 16 df -2.7050 difference (Prada - Oracle) 0.7196 standard error of difference 0 hypothesized difference -3.76 t .0017 p-value (two-tailed) -4.2304 confidence interval 95.% lower -1.1796 confidence interval 95.% upper 1.5254 margin of error 2. The Willow Run Outlet Mall has two Haggar Outlet Stores,...
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...Research, Statistics, and Psychology Kathy A. Abeyatunge University of Phoenix Research, Statistics, and Psychology The field of psychology is described as the study of mental processes and behaviors using methods of scientific research. In their attempt to substantiate or invalidate their hypotheses psychologists employ the uses of two significant tools, research and statistics. Research helps us delve through the complex nature of the human psyche; permitting us to categorizing symptoms of psychological disorders and providing us with an understanding of ourselves and how we relate to the world. Statistics is the mathematical product of research findings. It is the recorded data that aids in the identification of truth. This paper will look into the role research and statistics have on the field of psychology, as well as define the scientific method and provide a comparative analysis of primary and secondary data. Research in the scientific sense is not akin to the everyday search for knowledge that human beings conduct through personal observation. Instead scientific research relies on logical methodology. “The scientific approach is characterized by four ideals: curiosity, skepticism, objectivity, and critical thinking.” These ideals are the basic structure referred to as the scientific method and in application they consist of a series of steps to ensure accurate results. Step 1) Observation. This is simply interest shown in answering a question about an...
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...Week Four: Answer Questions about Hypothesis Testing For an H0 to be rejected, there has to be a proven relationship between groups. For an alternative Ha to be proven, there has to be a relationship explainable by the data. An example of an H0 would be that there is no difference in production output between workers who receive a pay increase compared to those who do not. A one tail test for this H0 would be no change in a worker's production output after a pay increase. A two-tail test would show there is a change in production output, increase or decrease, after a pay increase. With an of 0.05, the p-value for a two-tail set of data is 0.025, half of the total p-value in order to account for both sides of the distribution extremes. For the researcher to reject the H0, meaning that there is a statistically significant relationship between sides, the p-value cannot be greater than 0.025. An of and .932 p-value. The is the chance a Type I error will cause the H0 to be rejected because a treatment or condition influences the data when, in actuality, there is no difference in the data between groups. An example would be if the researcher wanted to know if receiving a pay increase improved the productivity levels of a worker, month over month. The Type I error would be in rejecting the H0 because the productivity levels decreased month over month, when in fact, the decrease was due to a lack of consumer demand instead. Consumer demand drives production levels which...
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...11. List the five steps of hypothesis testing, and explain the procedure and logic of each. Step 1: Restate the Question as a Research Hypothesis and a Null Hypothesis about the Populations. You want to restate the question as research hypothesis and null hypothesis about the populations because it allows you to think of two different samples. The research hypothesis and the null are opposite of each other. One is true and the other is not. The researcher predicts something and researches it and the null hypothesis says there will be no difference if what the researcher predicts. The logic is figuring out the probability of getting a particular result if the null hypothesis is true. Step 2: Determine the Characteristics of the Comparison Distribution In the hypothesis-testing process, you compare the actual sample’s score to this comparison distribution. The comparison distribution is the distribution that represents the population situation if the null hypothesis is true. If the null is true both samples will have a normal curve. Step 3: Determine the Cutoff Sample Score on the Comparison Distribution at Which the Null Hypothesis Should Be Rejected You will need Z scores and percentages, if a researcher decides that the score is lower than a certain percent then they would reject the null. Psychology researchers use a cutoff on the comparison distribution with a probability of 5% that a score will be at least that extreme if the null hypothesis were true. They are described...
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...PSY/315 March 4, 2013 Chapter 4 Practice Problems (11) List the five steps of hypothesis testing, and explained the procedure and logic of each. 1) Restate the research question; specify the null theory about the populations. State the null theory and the alternate theory Null: Ho: Alteration: Ha: 2) Determine the features of the compared distribution. Define the level of significance, using type 1 errors; identify sample size using data and resources that are available. 3) Define the region cutoff sample score. Identify the test statistics and sampling distributions. 4) Determine the sample’s score on the comparison distribution. Collect any data and compute the statistics test to find p -value 5) Select the appropriate theory. Classify the p-value and identify whether not to reject the null theory. Summarize the results and give a clear comprehensive solution towards the underline problem. (14) Based on the information given for each of the following studies; decide whether to reject the null hypothesis. For each, give (a) the Z- score cutoff (or cutoffs) on the comparison distribution at which the null hypothesis should be rejected (b) the Z score on the comparison distribution for the sample score and (c) your conclusion. Assume that all populations are normally distributed. Study A-D mean population = 5 Standard deviation = 1 Sample score = 7 P = study A&B =.05 P = study C&D = .01 Tails of this study a = 1(high prediction) Study...
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...Ch.1. Review Amber Hennrich May 26, 2014 12. Explain and give an example for each of the following types of variables: (a) equal-interval, (b) rank-order, (c) nominal, (d) ratio scale, (e) continuous. A) An equal-interval is a variable in which numbers stand for approximately equals amounts of what is being measured. Example: Grade Point Average B) A rank-order variable is numeric and the numbers stand only for the relative ranking. Example: A graduate standing in their class. Their GPA makes a big difference for instance if they stand first or second in the class. C) A nominal variable is not numeric and values are names or categories. Example: A nominal variable for gender would be female and male. D) A ratio scale is measured by equal-interval variable. An equal-interval variable has an absolute zero point on the ratio scale. An absolute zero point means there is an absence of the variable. Example: A number of cats an individual has. If one person has three and the other has six, you can say that they have three times the amount of that person. E) A continuous variable is a theory that you can have an infinite number between 2 variables. Example: An example of this would big age. You can say you are 12.5 years old. 15. Make (a) a frequency table and (b) a histogram. Then (c) describe the general shape of the distribution. A) Speeds | Frequency | Percent | 15-21 | 2 | 5% | 22-28 | 4 | 10% | 29-35 | 17 | 42.50% | 36-42 | 13 | 32.50% | ...
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...Week 4 Individual Assignment Erwin O. Raymer III PSY/315 Jan. 13th 2014 Jennifer Lapin Week 4 Individual Assignment The five steps of hypothesis testing consist of the following. Restate the question as a research hypothesis and a null hypothesis. This is where an individual would make a research hypothesis, which is basically a prediction intended to be tested in a research study. This prediction is usually based on the researcher’s theory. A null hypothesis is the opposite of the research hypothesis. If the null hypothesis is found to be true then it is not possible for the research hypothesis to be relevant. Same goes for if the research hypothesis is true then the null hypothesis is unable to be relevant as well. Determine the characteristics of the comparison distribution. In the hypothesis testing process you want to find out the probability that you could have a sample score as extreme as what you got if your sample was from a population with a distribution of the sort you would have if the null hypothesis were true. That is in the hypothesis testing process, you compare the actual samples score to this comparison distribution. Determine the cut off sample score on the comparison distribution at which the null hypothesis should be rejected. (Critical value) Ideally, before conducting a study, researchers set a target against which they will compare their results. How extreme a sample score they would need to decide against...
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...PSY/315 March 18, 2013 Chapter 7 14.) Evolutionary theory often emphasizes that human have adapted to their physical environment. One such theory hypothesizes that people should spontaneously follow a 24-hour cycle of sleeping and waking-even though they are not exposed to the usual pattern of sunlight. To test this notion, eight paid volunteers were placed (individually) in a room in which there were no light from outside and no clocks or other indications of time. They could turn the lights on and off is they wish. After a month in the room, each individual tended to develop a study cycle. Their cycles at the end of the study were as follows: 25, 27, 25, 23, 24, 25, 26, and 25. Using the 0 .5 level of significance, what should we conclude about the theory that 24 hours is the natural cycle? (That is, does the average cycling under these conditions differ significantly from 24-hour?) (a) Use the steps of hypothesis testing. (b) Sketch the distributions involved, (c) explain yourself to someone who has never had a course in statistics. (a) Steps of hypothesis testing 1. Restate the question as a research hypothesis and a null hypothesis about the populations. There are two populations Population 1: people who are given the experimental test for 24 hours is the natural cycle. Population 2: people who are given the experimental test in less than 24 hours is the natural cycle. The null hypothesis: µ = 24 The alternative hypothesis: µ ≠ 24 2. Define the...
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...Statistics for Psychology Mary Hale 7/8/2013 PSY 315 Dr. Ellis-Morris Prepare a written response to the following assignments located in the text: Ch. 1, Practice Problems: 12, 15, 19, 20, 21, & 22 (12) Explain and give an example for each of the following types of variables: A) equal interval- A variable whose value is not known and can take on different values. For example 0 degrees Celsius or Fahrenheit (0 degrees Celsius does not mean there is no temperature but it is different from 0 degrees Fahrenheit.) B) rank order- variables that are individual observations that can be put into order from smallest to largest, even though the exact values are unknown. An example of this would be shirts, small, medium and large shirts. C) Nominal- variables which are also called categorical variables. They classify observations into a small number of categories. Examples are 1) "types of property" can include houses, condos, Co-ops, or bungalows. Another example 2) Gender or race D) Ratio Scale- is measured data with a zero point and provides information relative to an absolute zero. An example of this is a person's weight. The scale starts at 0 and when you step on it, the amount goes up starting from 0 to the amount of weight on it. (It has to start at 0). E) Continuous- variables that are numeric and can be any number (positive or negative). Examples of...
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... Madame President Herrera, Now that you have learned how the Justices can influence the decision-making process and have learned how the nomination process essentially works, we now want to turn to an area that she will want to be weary of when choosing two particular nominees. We call this area that you want to watch out for “red flags.” There are many different red flags that can indicate a potential nominee is going to not be the right choice. First, as the president she will want to check out the all the nominee’s ethical backgrounds and expertise. President Herrera will want to make sure they are as qualified as they can be before suggesting them as a nominee. Lawrence Baum, a credible source yet again outlines this, “to minimize the possibility of such embarrassments, administrations today give close scrutiny to the competence and ethics of potential nominees” (Baum, p. 36). She will want to look for issues that may come out later to the public, and avoid them at all costs. Such issues can be classified as sexual harassment or violations of laws that a potential nominee engaged. If this is the case then she should not considered them nomination. Also, the President does not want to find out ten years from now that one of the Justices she nominated was in violation of the law. Instead, look for the most qualified candidates upfront because they will be of the most value to her. Second, another red flag is a nominee who is too dominated by his or her political party...
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...Question 3 a) Although all the ratings are measured based on the same scale (thus, same unit), the scores of the variables have various means and standard deviations, indicating that the rating of each variable distributes differently from one another on the scale. Standardizing the data makes the means of the variables equal to zero and standard deviations to one. The standardization realizes the subsequent analysis of the correlation matrix and makes it easier to interpret the principal components derived later. b) The large correlations between each pair of the ratings are listed in the table below. The variables are defined as follows: Diversions: the diversity of the residents in terms of race and ethnicity. House: the cost of housing for ownership or rent. Transportation: the convenience of traveling between places. Large correlation (r over ±0.5) Make sense? Why? Yes No Diversions & House (r = -0.5267) Since the data are collected from small cities in the US, there is chance that most of these cities have developed from a college town. Thus, the resident population should comprise many international students, faculty and staff. Usually, these people, and also American college students, are not willing or not able to spend much on the rent or to own a house. Diversions & Transportation (r = 0.5045) Again, a college town usually provides a well public transportation system for students to commute from place to place. Education & House ...
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